diff --git a/algebird-core/src/main/scala/com/twitter/algebird/HyperLogLogSeries.scala b/algebird-core/src/main/scala/com/twitter/algebird/HyperLogLogSeries.scala
new file mode 100644
index 000000000..ead3f8536
--- /dev/null
+++ b/algebird-core/src/main/scala/com/twitter/algebird/HyperLogLogSeries.scala
@@ -0,0 +1,70 @@
+/*
+Copyright 2014 Twitter, Inc.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+*/
+
+package com.twitter.algebird
+
+case class HLLSeries(bits: Int, rows: Vector[Map[Int, Long]]) {
+  def since(threshold: Long) =
+    HLLSeries(
+      bits,
+      rows.map{ _.filter{ case (j, ts) => ts >= threshold } })
+
+  def toHLL: HLL =
+    if (rows.isEmpty)
+      SparseHLL(bits, Map())
+    else
+      rows.zipWithIndex.map{
+        case (map, i) =>
+          SparseHLL(bits, map.mapValues{ ts => Max((i + 1).toByte) }): HLL
+      }.reduce{ _ + _ }
+}
+
+class HyperLogLogSeriesMonoid(val bits: Int) extends Monoid[HLLSeries] {
+  import HyperLogLog._
+
+  val zero = HLLSeries(bits, Vector())
+
+  def create(example: Array[Byte], timestamp: Long): HLLSeries = {
+    val hashed = hash(example)
+    val (j, rhow) = jRhoW(hashed, bits)
+
+    val vector = Vector.fill(rhow - 1){ Map[Int, Long]() } ++ Vector(Map(j -> timestamp))
+    HLLSeries(bits, vector)
+  }
+
+  def plus(left: HLLSeries, right: HLLSeries): HLLSeries = {
+    if (left.rows.size > right.rows.size)
+      plus(right, left)
+    else {
+      val zipped = left.rows.zip(right.rows).map{
+        case (l, r) =>
+          combine(l, r)
+      }
+      HLLSeries(
+        bits,
+        zipped ++ right.rows.slice(left.rows.size, right.rows.size))
+    }
+  }
+
+  private def combine(left: Map[Int, Long], right: Map[Int, Long]): Map[Int, Long] = {
+    if (left.size > right.size)
+      combine(right, left)
+    else {
+      right ++
+        left.map{ case (k, v) => k -> (right.getOrElse(k, 0L).max(v)) }
+    }
+  }
+}
diff --git a/algebird-test/src/test/scala/com/twitter/algebird/HyperLogLogSeriesTest.scala b/algebird-test/src/test/scala/com/twitter/algebird/HyperLogLogSeriesTest.scala
new file mode 100644
index 000000000..6e2fa4ec3
--- /dev/null
+++ b/algebird-test/src/test/scala/com/twitter/algebird/HyperLogLogSeriesTest.scala
@@ -0,0 +1,63 @@
+package com.twitter.algebird
+
+import org.scalatest._
+
+import org.scalacheck.{ Gen, Arbitrary }
+
+import HyperLogLog._ //Get the implicit int2bytes, long2Bytes
+
+class HyperLogLogSeriesLaws extends CheckProperties {
+  import BaseProperties._
+
+  implicit val hllSeriesMonoid = new HyperLogLogSeriesMonoid(5) //5 bits
+
+  implicit val hllSeriesGen = Arbitrary {
+    for (
+      v <- Gen.choose(0, 10000)
+    ) yield (hllSeriesMonoid.create(v, v))
+  }
+
+  property("HyperLogLogSeries is a Monoid") {
+    monoidLawsEq[HLLSeries]{ _.toHLL == _.toHLL }
+  }
+}
+
+class HyperLogLogSeriesTest extends WordSpec with Matchers {
+  def getHllCount[T <% Array[Byte]](it: Iterable[T], hll: HyperLogLogMonoid) = {
+    hll.sizeOf(hll.sum(it.map { hll(_) })).estimate.toDouble
+  }
+
+  def aveErrorOf(bits: Int): Double = 1.04 / scala.math.sqrt(1 << bits)
+
+  def testApproximatelyEqual(hllSeries: HLLSeries, hllCount: Double, bits: Int) = {
+    val seriesResult = hllSeries.toHLL.estimatedSize
+    assert(scala.math.abs(seriesResult - hllCount) / seriesResult < (3.5 * aveErrorOf(bits)))
+  }
+
+  "HyperLogLogSeries" should {
+    "properly calculate .since" in {
+      val bits = 12
+      val hllSeriesMonoid = new HyperLogLogSeriesMonoid(bits)
+      val hll = new HyperLogLogMonoid(bits)
+
+      val timestamps = (1 to 100).map { _.toLong }
+      val r = new java.util.Random
+      val timestampedData = timestamps.map { t => (r.nextLong, t) }
+
+      val series = timestampedData
+        .map{ case (value, timestamp) => hllSeriesMonoid.create(value, timestamp) }
+        .reduce{ hllSeriesMonoid.plus(_, _) }
+
+      timestamps.foreach { timestamp =>
+        val seriesResult = series.since(timestamp)
+
+        val dataSinceTimestamp = timestampedData
+          .dropWhile { case (_, t) => t < timestamp }
+          .map { case (value, _) => value }
+        val expected = getHllCount(dataSinceTimestamp, hll)
+
+        testApproximatelyEqual(seriesResult, expected, bits)
+      }
+    }
+  }
+}